There are multiple approaches for steel bar inspection. One way is eddy current testing (ECT). Eddy current testing (ECT) has been a major approach in surface flaw detection for steel bars, for example as seen by reference to U.S. Pat. No. 6,850,056 issued to Fujisaki and Tomita entitled FLAW DETECTION DEVICE FOR STEEL BAR, hereby incorporated by reference in its entirety. ECT involves inducing an eddy current in the surface of the steel bar by way of an alternating current (AC) coil. The induced eddy current is detected using a detecting coil or the like to produce an eddy current signal. Flaws in the metal bar are detected through assessment of the magnitude and the phase of the detected eddy current signal. Another way to inspect involves use of vision or imaging systems. Vision or imaging based systems assess images taken of the steel bar for the purpose of detecting flaws or surface defects, as seen by reference to U.S. Pat. No. 7,324,681 issued to Chang et al. entitled APPARATUS AND METHOD FOR DETECTING SURFACE DEFECTS ON A WORKPIECE, SUCH AS A ROLLED/DRAWN METAL BAR, hereby incorporated by reference in its entirety. The assessment performed by image-based flaw detection may involve locating areas of contrast for example. Each flaw detection approach mentioned above, however, has its own unique characteristics.
For instance, due to the detection characteristics of ECT, it may not be able to effectively detect longitudinal types of surface flaws. Another characteristic of ECT is that it generally provides no visual feedback as to the exact nature of the detected flaw on the bar surface unless the detected locations are physically reviewed by a human being. In many primary applications, such as in hot rolling lines where bars are red hot even after inspection, or cold drawing lines where each bar could be hundreds of meters long, physical review is very difficult, if not impossible. A further characteristic of ECT, however, is that it provides some degree of depth information of the surface flaws themselves. On the other hand, one characteristic of an imaging based system is its ability to reliably detect longitudinal types of surface flaws as well as provide visual feedback as to the exact nature of the detected flaw. However, imaging-based systems in general may be limited in their ability to provide good depth information concerning detected flaws. Nonetheless, imaging based systems are known to provide near real-time, direct and intuitive visual feedback to the system operators of the detected flaws, allowing easy, although manual, flaw verification (i.e., an actual image of the flow site can be saved and made available later, which can then be used by an operator to visually verify a machine-detected flaw) and/or automatic image classification through advanced algorithms such as neural network, heuristic rules or support vector machines.
FIGS. 4A and 4B illustrate examples of a user interface for a conventional computer-based ECT data rendering system. FIG. 4A shows a screen 200, which displays a time series of the ECT data, indicated generally as ECT data 204, in an X-Y graph format, as is typical. The X-axis represents “time” and the Y-axis represents the magnitude (strength) of the ECT signal. The user interface is typically configured to allow users to preset one or more strength thresholds indicative of a detected flaw. Such thresholds may be displayed as horizontal lines, for example as indicated by reference numerals 202L and 202U for lower and upper threshold levels, respectively. Any ECT signal 204 that has a magnitude (strength) higher than a threshold level is considered a surface flaw detection event. For instance, when the ECT signal 204 exceeds the lower threshold level 202L at location 206, the ECT rendering system considers this a surface flaw detection event. Likewise, when the ECT signal 204 exceeds the upper threshold level 202U at location 208, the ECT rendering system would also consider this a surface flaw detection event. Typically, the higher the strength of the ECT signal that triggered the flaw detection event, the greater the severity of the flaw.
FIG. 4B shows a companion display to FIG. 4A. At any given moment of the ECT data 204, a corresponding phase diagram 210 may be generated and displayed by the data rendering system. In this case, a trace pattern 214 is displayed based on the phase of the detected eddy current signal (i.e., relative to the inducing signal). Just like the magnitude, the user interface provides the user with the ability to set severity thresholds, such as phase threshold 212, which are used to detect the existence of a flaw.
FIG. 5 shows an example of a user interface for a conventional computer-based image-data rendering system. A concept (not shown) may involve display of a single bar chart representing the inspected metal bar, with markings (i.e., “X”) indicating at what longitudinal positions flaws have been detected. FIG. 5, on the other hand, shows a screen 300 of a user interface with a more detailed approach for displaying the inspection results. An imaging system may have multiple imaging sensors (i.e., cameras) to cover the entire circumference of the metal bar. Accordingly, the screen 300 may include a pie chart, shown in the upper left, to indicate diagrammatically the respective circumferential coverage of each one of the cameras. The screen 300 shows an extension of the single bar chart concept described above, wherein flaws (e.g., items 304, 306 marked with an “X”) detected from the different image streams (i.e., different cameras) are marked on separate bar charts associated with respective cameras. This extended approach provides the user with additional circumferential information about the detection data. The screen 300 may also show (i) the direction of the movement of the metal bar, indicated by the arrow 102, as well as (ii) its speed.
With continued reference to FIG. 5, the screen 300 may also include a flaw list pane 310 which shows the inventory of the detected flaws/defects, and which may include for each flaw a variety of information, such as its respective type, size, shape and the like. The interface shown in screen 300 may also be configured to allow a user to navigate through the pane 310 and select one of the listed flaws. The interface is configured to then obtain and display more detailed information about the selected flaw. For example, the screen 300 may have a separate, additional image pane configured to display an actual image (item 302) of the metal bar inclusive of and surrounding a flaw site (item 308). Moreover, a flaw selected in pane 310 may cause its specific longitudinal position on the metal bar to be displayed on the screen 300 near the bar charts, as shown near the selected flaw 304. Notwithstanding all the information available in an image-based detection system, it would nonetheless be desirable for a user to have improved depth information concerning the detected flaws.
There is therefore a need for an inspection system that overcomes one or more of the problems or shortcoming described above.